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For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds., (© 2022 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

The ongoing global decline in vulture populations raises major conservation concerns, but little is known about the factors that mediate scavenger habitat use, in particular the importance of abundance of live prey versus prey mortality. We test this using data from the Serengeti-Mara ecosystem in East Africa. The two hypotheses that prey abundance or prey mortality are the main drivers of vulture habitat use provide alternative predictions. If vultures select areas based only on prey abundance, we expect tracked vultures to remain close to herds of migratory wildebeest regardless of season. However, if vultures select areas where mortality rates are greatest then we expect vultures to select the driest regions, where animals are more likely to die of starvation, and to be attracted to migratory wildebeest only during the dry season when wildebeest mortality is greatest. We used data from GSM-GPS transmitters to assess the relationship between three vulture species and migratory wildebeest in the Mara-Serengeti ecosystem. Results indicate that vultures preferentially cluster around migratory herds only during the dry season, when herds experience their highest mortality. Additionally during the wet season, Ruppell's and Lappet-faced vultures select relatively dry areas, based on Normalized Difference Vegetation Index, whereas White-backed vultures preferred wetter areas during the wet season. Differences in habitat use among species may mediate coexistence in this scavenger guild. In general, our results suggest that prey abundance is not the primary driver of avian scavenger habitat use. The apparent reliance of vultures on non-migratory ungulates during the wet season has important conservation implications for vultures in light of on-going declines in non-migratory ungulate species and use of poisons in unprotected areas.

Understanding the movements of animals is pivotal for understanding their ecology and predicting their survival in the face of rapid global changes to climate, land use, and habitats, thus facilitating more effective habitat management. Migration by flying animals is an extreme form of movement that may be especially influenced by weather. With satellite telemetry studies, and the growing availability of information about the Earth's weather and land surface conditions, many data are collected that can advance our understanding about the mechanisms that shape migrations. We present the track annotation approach for movement data analysis using information about weather from the North American Reanalysis data set, a publicly available, regional, high-resolution model-observation hybrid product, and about topography, from a publicly available high-resolution digital elevation model (DEM). As a case study, we present the analysis of the response to environmental conditions in three contrasting populations of Turkey Vultures (Cathartes aura) across North America, tracked with a three-dimensional GPS-based sensor. Two populations in the east and west coasts of the United States responded similarly to weather, indicating use of both slope and thermal soaring. Continental-interior, "Plains populations," exhibited a different migratory pattern primarily indicative of thermal soaring. These differences help us understand the constraints and behaviors of soaring migrants. The track annotation approach allowed large-scale comparative study of movement in an important migratory species, and will enable similar studies at local to global scales.

Migratory bird needs must be met during four phases of the year: breeding season, fall migration, wintering, and spring migration; thus, management may be needed during all four phases. The bulk of research and management has focused on the breeding season, although several issues remain unsettled, including the spatial extent of habitat influences on fitness and the importance of habitat on the breeding grounds used after breeding. Although detailed investigations have shed light on the ecology and population dynamics of a few avian species, knowledge is sketchy for most species. Replication of comprehensive studies is needed for multiple species across a range of areas, Information deficiencies are even greater during the wintering season, when birds require sites that provide security and food resources needed for survival and developing nutrient reserves for spring migration and, possibly, reproduction. Research is needed on many species simply to identify geographic distributions, wintering sites, habitat use, and basic ecology. Studies are complicated, however, by the mobility of birds and by sexual segregation during winter. Stable-isotope methodology has offered an opportunity to identify linkages between breeding and wintering sites, which facilitates understanding the complete annual cycle of birds. The twice-annual migrations are the poorest-understood events in a bird's life. Migration has always been a risky undertaking, with such anthropogenic features as tall buildings, towers, and wind generators adding to the risk. Species such as woodland specialists migrating through eastern North America have numerous options for pausing during migration to replenish nutrients, but some species depend on limited stopover locations. Research needs for migration include identifying pathways and timetables of migration, quality and distribution of habitats, threats posed by towers and other tall structures, and any bottlenecks for migration. Issues such as human population growth, acid deposition, climate change, and exotic diseases are global concerns with uncertain consequences to migratory birds and even less-certain remedies. Despite enormous gaps in our understanding of these birds, research, much of it occurring in the past 30 years, has provided sufficient information to make intelligent conservation efforts but needs to expand to handle future challenges.

We develop individual-based movement ecology models (MEM) to explore turkey vulture (Cathartes aura) migration decisions at both hourly and daily scales. Vulture movements in 10 migration events were recorded with satellite-reporting GPS sensors, and flight behavior was observed visually, aided by on-the-ground VHF radio-tracking. We used the North American Regional Reanalysis dataset to obtain values for wind speed, turbulent kinetic energy (TKE), and cloud height and used a digital elevation model for a measure of terrain ruggedness. A turkey vulture fitted with a heart-rate logger during 124 h of flight during 38 contiguous days showed only a small increase in mean heart rate as distance traveled per day increased, which suggests that, unlike flapping, soaring flight does not lead to greatly increased metabolic costs. Data from 10 migrations for 724 hourly segments and 152 daily segments showed that vultures depended heavily upon high levels of TKE in the atmospheric boundary layer to increase flight distances and maintain preferred bearings at both hourly and daily scales. We suggest how the MEM can be extended to other spatial and temporal scales of avian migration. Our success in relating model-derived atmospheric variables to migration indicates the potential of using regional reanalysis data, as here, and potentially other regional, higher-resolution, atmospheric models in predicting changing movement patterns of soaring birds under various scenarios of climate and land use change.